Triple
T38008528
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pabst Brewing Company |
E948299
|
entity |
| Predicate | product |
P490
|
FINISHED |
| Object |
Lone Star Beer
Lone Star Beer is a classic American lager often called "The National Beer of Texas," known for its long association with Texas culture and heritage.
|
E2251021
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Lone Star Beer | Statement: [Pabst Brewing Company, product, Lone Star Beer]
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Lone Star Beer Triple: [Pabst Brewing Company, product, Lone Star Beer]
Generated description
Lone Star Beer is a classic American lager often called "The National Beer of Texas," known for its long association with Texas culture and heritage.
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f76efb4b10819092c8c2ba28ac06a8 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbc942d2808190923ecb1dc12a1b66 |
completed | May 6, 2026, 11:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a412cc965a08190828bd4f5c4475b2a |
completed | June 28, 2026, 2:16 p.m. |
| NEDg | Description generation | batch_6a413262da508190b80c01ab82eab4c3 |
completed | June 28, 2026, 2:40 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a41331ec70881908eaa4d67413c7c39 |
completed | June 28, 2026, 2:43 p.m. |
Created at: May 3, 2026, 4:20 p.m.